Validation of a Genetic-Enhanced Risk Prediction Model for Colorectal Cancer in a Large Community-Based Cohort

Yu Ru Su*, Lori C. Sakoda, Jihyoun Jeon, Minta Thomas, Yi Lin, Jennifer L. Schneider, Natalia Udaltsova, Jeffrey K. Lee, Iris Lansdorp-Vogelaar, Elisabeth F.P. Peterse, Ann G. Zauber, Jiayin Zheng, Yingye Zheng, Elizabeth Hauser, John A. Baron, Elizabeth L. Barry, D.T. Bishop, Hermann Brenner, Daniel D. Buchanan, Andrea Burnett-HartmanPeter T. Campbell, Graham Casey, Sergi Castellví-Bel, Andrew T. Chan, Jenny Chang-Claude, Jane C. Figueiredo, Steven J. Gallinger, Graham G. Giles, Stephen B. Gruber, Andrea Gsur, Marc J. Gunter, Jochen Hampe, Heather Hampel, Tabitha A. Harrison, Michael Hoffmeister, Xinwei Hua, Jeroen R. Huyghe, Mark A. Jenkins, Temitope O. Keku, Loic Le Marchand, Li Li, Annika Lindblom, Victor Moreno, Polly A. Newcomb, Paul D.P. Pharoah, Elizabeth A. Platz, John D. Potter, Conghui Qu, Gad Rennert, Robert E. Schoen, Martha L. Slattery, Mingyang Song, Fränzel J.B. van Duijnhoven, Bethany Van Guelpen, Pavel Vodicka, Alicja Wolk, Michael O. Woods, Anna H. Wu, Richard B. Hayes, Ulrike Peters*, Douglas A. Corley*, Li Hsu*

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

Polygenic risk scores (PRS) which summarize individuals' genetic risk profile may enhance targeted colorectal cancer screening. A critical step towards clinical implementation is rigorous external validations in large community-based cohorts. This study externally validated a PRS-enhanced colorectal cancer risk model comprising 140 known colorectal cancer loci to provide a comprehensive assessment on prediction performance. METHODS: The model was developed using 20,338 individuals and externally validated in a community-based cohort (n = 85,221). We validated predicted 5-year absolute colorectal cancer risk, including calibration using expected-to-observed case ratios (E/O) and calibration plots, and discriminatory accuracy using time-dependent AUC. The PRS-related improvement in AUC, sensitivity and specificity were assessed in individuals of age 45 to 74 years (screening-eligible age group) and 40 to 49 years with no endoscopy history (younger-age group). RESULTS: In European-ancestral individuals, the predicted 5-year risk calibrated well [E/O = 1.01; 95% confidence interval (CI), 0.91-1.13] and had high discriminatory accuracy (AUC = 0.73; 95% CI, 0.71-0.76). Adding the PRS to a model with age, sex, family and endoscopy history improved the 5-year AUC by 0.06 (P < 0.001) and 0.14 (P = 0.05) in the screening-eligible age and younger-age groups, respectively. Using a risk-threshold of 5-year SEER colorectal cancer incidence rate at age 50 years, adding the PRS had a similar sensitivity but improved the specificity by 11% (P < 0.001) in the screening-eligible age group. In the younger-age group it improved the sensitivity by 27% (P = 0.04) with similar specificity. CONCLUSIONS: The proposed PRS-enhanced model provides a well-calibrated 5-year colorectal cancer risk prediction and improves discriminatory accuracy in the external cohort. IMPACT: The proposed model has potential utility in risk-stratified colorectal cancer prevention.

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